Machine Learning Methods for Demand Estimation
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Note: DOI: 10.1257/aer.p20151021
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References listed on IDEAS
- Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2014.
"High-Dimensional Methods and Inference on Structural and Treatment Effects,"
Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 29-50, Spring.
- Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2013. "High dimensional methods and inference on structural and treatment effects," CeMMAP working papers CWP59/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Alexandre Belloni & Victor Chernozhukov & Christian Hansen, 2013. "High dimensional methods and inference on structural and treatment effects," CeMMAP working papers 59/13, Institute for Fiscal Studies.
- Patrick Bajari & Denis Nekipelov & Stephen P. Ryan & Miaoyu Yang, 2015. "Demand Estimation with Machine Learning and Model Combination," NBER Working Papers 20955, National Bureau of Economic Research, Inc.
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More about this item
JEL classification:
- C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
- D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
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